AI Medical Compendium Topic:
Clinical Competence

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Gastroenterologist-Level Identification of Small-Bowel Diseases and Normal Variants by Capsule Endoscopy Using a Deep-Learning Model.

Gastroenterology
BACKGROUND & AIMS: Capsule endoscopy has revolutionized investigation of the small bowel. However, this technique produces a video that is 8-10 hours long, so analysis is time consuming for gastroenterologists. Deep convolutional neural networks (CNN...

Performance of a Deep-Learning Neural Network to Detect Intracranial Aneurysms from 3D TOF-MRA Compared to Human Readers.

Clinical neuroradiology
PURPOSE: To study the clinical potential of a deep learning neural network (convolutional neural networks [CNN]) as a supportive tool for detection of intracranial aneurysms from 3D time-of-flight magnetic resonance angiography (TOF-MRA) by comparing...

Handheld laparoscopic robotized instrument: progress or challenge?

Surgical endoscopy
BACKGROUND: Handheld laparoscopic robotized instruments have been developed to combine the advantages of a robotic operation system and conventional laparoscopic instruments. Direct objective standards are needed to quantify surgeons' skill level and...

Artificial Intelligence in Medical Education: Best Practices Using Machine Learning to Assess Surgical Expertise in Virtual Reality Simulation.

Journal of surgical education
OBJECTIVE: Virtual reality simulators track all movements and forces of simulated instruments, generating enormous datasets which can be further analyzed with machine learning algorithms. These advancements may increase the understanding, assessment ...

Machine learning classifiers can predict Gleason pattern 4 prostate cancer with greater accuracy than experienced radiologists.

European radiology
OBJECTIVE: The purpose of this study was: To test whether machine learning classifiers for transition zone (TZ) and peripheral zone (PZ) can correctly classify prostate tumors into those with/without a Gleason 4 component, and to compare the performa...

Concepts in U.S. Food and Drug Administration Regulation of Artificial Intelligence for Medical Imaging.

AJR. American journal of roentgenology
Although extensive attention has been focused on the enormous potential of artificial intelligence (AI) technology, a major question remains: how should this fundamentally new technology be regulated? The purpose of this article is to provide an ove...

Deep Learning-Assisted Diagnosis of Cerebral Aneurysms Using the HeadXNet Model.

JAMA network open
IMPORTANCE: Deep learning has the potential to augment clinician performance in medical imaging interpretation and reduce time to diagnosis through automated segmentation. Few studies to date have explored this topic.

MCRDR Knowledge-Based 3D Dialogue Simulation in Clinical Training and Assessment.

Journal of medical systems
Dialogue-based simulation is a real-world practice technique for medical and clinical education that provides students with an opportunity to train using hands-on experiences without putting actual patients being put at risk. In this paper, a 3D inte...

Video-based surgical skill assessment using 3D convolutional neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: A profound education of novice surgeons is crucial to ensure that surgical interventions are effective and safe. One important aspect is the teaching of technical skills for minimally invasive or robot-assisted procedures. This includes the ...